Technical Reports

[2025]

  • D’Acunto, G., Di Lorenzo, P., & Barbarossa, S. (2025). The Causal Abstraction Network: Theory and Learning. [preprint]

Accepted/Published

[2026]

  • D’Acunto, G., Di Lorenzo, P., & Barbarossa, S. (2026). Learning Consistent Causal Abstraction Networks. To be published on the Proceedings of 2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2026, May 4-8, Barcelona, Spain) [paper]

  • Di Nino, L., D’Acunto, G., Di Lorenzo, P., & Barbarossa, S. (2026). Learning the Structure of Connection Graphs. To be published on the Proceedings of 2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2026, May 4-8, Barcelona, Spain) [paper]

  • Marinucci, L., D’Acunto, G., Di Lorenzo, P., & Barbarossa, S. (2026). Simplicial Gaussian Models: Representation and Inference. To be published on the Proceedings of 2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2026, May 4-8, Barcelona, Spain) [paper]

[2025]

  • Marinucci, L., Di Nino, L., D’Acunto, G., Pandolfo, M. E., Di Lorenzo, P., & Barbarossa, S. (2025). Colored Markov Random Fields for Probabilistic Topological Modeling. To be published on the Proceedings of 2025 59th Asilomar Conference on Signals, Systems, and Computers (Asilomar 2025, October 26-29, Pacific Grove, CA, USA) [paper]

  • Grimaldi, E., Pandolfo, M. E., D’Acunto, G., Barbarossa, S., & Di Lorenzo, P. (2025). Learning Network Sheaves for AI-native Semantic Communication. To be published on the Proceedings of 2025 59th Asilomar Conference on Signals, Systems, and Computers (Asilomar 2025, October 26-29, Pacific Grove, CA, USA) [paper]

  • D’Acunto, G., Battiloro, C. (2025). The Relativity of Causal Knowledge. In Proceedings of the 41st Conference on Uncertainty in Artificial Intelligence (UAI 2025, July 21-25, Rio de Janeiro, Brasil) [paper]

  • D’Acunto, G., Zennaro, F. M., Felekis, Y., & Di Lorenzo, P. (2025). Causal Abstraction Learning based on the Semantic Embedding Principle. In Proceeding of the 42nd International Conference on Machine Learning (ICML 2025, July 13-18, Vancouver, Canada) [paper]

[2024]

  • D’Acunto, G., Di Lorenzo, P., Bonchi, F., Sardellitti, S., & Barbarossa, S. (2024, July). Learning Multi-Frequency Partial Correlation Graphs. In IEEE Transactions on Signal Processing, vol. 72, pp. 2953-2969, 2024, doi: 10.1109/TSP.2024.3401072. [paper]

  • D’Acunto, G., Bonchi, F., De Francisci Morales, G., & Giovanni Petri (2024, January). Extracting the Multiscale Causal Backbone of Brain Dynamics. In Proceedings of the 3rd Conference on Causal Learning and Reasoning (CLeaR 2024, April 1-3, Los Angeles, USA)_, PMLR. [paper]

[2023]

  • D’Acunto, G., De Francisci Morales, G., Bajardi, P., & Bonchi, F. (2023, October). Learning Multiscale Non-stationary Causal Structures. In Transactions on Machine Learning Research. [paper]

  • D’Acunto, G., Di Lorenzo, P., & Barbarossa, S. (2023, October). Multiscale Causal Structure Learning. In Transactions on Machine Learning Research. [paper]

[2021]

  • D’Acunto, G., Bajardi, P., Bonchi, F., & De Francisci Morales, G. (2021, November). The evolving causal structure of equity risk factors. In Proceedings of the Second ACM International Conference on AI in Finance (pp. 1-8). [paper]